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김자랑 ( Kim Jarang ),정양수 ( Jung Yang-soo ) 한국현대영어영문학회 2016 현대영어영문학 Vol.60 No.4
The purpose of this study was to investigate whether there was a significant difference in the use of vocabulary learning strategies by middle school English learners according to students` vocabulary knowledge levels, and whether learners used different vocabulary learning strategies according to different types of vocabulary test. For this study, a questionnaire of vocabulary learning strategies was administered to 111 EFL learners in middle school in “D” city. As results of this study, followings were found. First, there was a significant difference in the use of vocabulary learning strategies according to students` levels. That is, advanced-level learners used more and various strategies in almost all categorized strategies than intermediate and lower level students. And it was found that the meaningdetermination strategies most frequently used while the social strategies was least used. Second, significant differences were not found in the use of vocabulary learning strategies according to different types of vocabulary tests regardless of students vocabulary proficiency levels. Also significant correlation between students` use of vocabulary learning strategies and types of vocabulary tests mostly was not found regardless of students` levels. If any, it was found that correlation coefficients were relatively weak. (Chungnam National University)
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TPE를 이용한 Triplet 추출 기반 질의응답 시스템
김자랑(JaRang Kim),김경수(KyungSoo Kim),최용석(YongSuk Choi) 한국정보과학회 2013 정보과학회 컴퓨팅의 실제 논문지 Vol.19 No.12
효과적인 질의응답 시스템의 구현을 위해서는 텍스트 코퍼스(Text Corpus)내의 문장을 의미적으로 분석하여 질의에 대한 구체적인 응답을 찾아내는 것이 중요하다. 본 연구에서는 패턴 트리의 효율적인 고속 패턴 매칭을 가능하게 하는 트리 패턴 표현식(Tree Pattern Expression : TPE)을 이용하여 문장의 주요 객체 정보를 Triplet 형태로 추출하고 이를 효과적으로 활용하는 고성능 질의응답 시스템을 제안한다. 실험을 통하여 TPE를 이용한 Triplet 추출 기법은 기존 질의응답 시스템에서 사용된 기법에 비해 Triplet을 더 효과적으로 추출할 수 있을 뿐만 아니라 Triplet 확장, Named Entity Tagging과 질의문 타입 분류 방법을 결합하여 보다 정확한 질의응답을 수행할 수 있음을 확인하였다. To implement question and answering system effectively, it is important to semantically analyze sentences in text corpus and find an exact answer to the question. In this paper, we suggest high-performance question and answering system that can efficiently extract desired information as triplet from sentence using Tree Pattern Expression(TPE). By using TPE, it is possible to match tree patterns speedy and accurately. In experiment, our question and answering system based on triplet using TPE is more effective than other conventional systems. Especially, our system shows much better performance when combined with triplet extension, named entity tagging and question type classification methods.
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